ArticleBMC health services research2012
Barriers and opportunities for evidence-based health service planning: the example of developing a Decision Analytic Model to plan services for sexually transmitted infections in the UK.
Article in BMC health services research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Healthcare provider and service user perspectives on STI risk reduction interventions for young people and MSM in the UK.Sexually transmitted infections · 2020Article
- Evidence-based medicine among health-care workers in hospitals in Iran: A nationwide survey.Journal of education and health promotion · 2020Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundDecision Analytic Models (DAMs) are established means of evidence-synthesis to differentiate between health interventions. They have mainly been used to inform clinical decisions and health technology assessment at the national level, yet could also inform local health service planning. For this, a DAM must take into account the needs of the local population, but also the needs of those planning its services. Drawing on our experiences from stakeholder consultations, where we presented the potential utility of a DAM for planning local health services for sexually transmitted infections (STIs) in the UK, and the evidence it could use to inform decisions regarding different combinations of service provision, in terms of their costs, cost-effectiveness, and public health outcomes, we discuss the barriers perceived by stakeholders to the use of DAMs to inform service planning for local populations, including (1) a tension between individual and population perspectives; (2) reductionism; and (3) a lack of transparency regarding models, their assumptions, and the motivations of those generating models. DISCUSSION: Technological advances, including improvements in computing capability, are facilitating the development and use of models such as DAMs for health service planning. However, given the current scepticism among many stakeholders, encouraging informed critique and promoting trust in models to aid health service planning is vital, for example by making available and explicit the methods and assumptions underlying each model, associated limitations, and the process of validation. This can be achieved by consultation and training with the intended users, and by allowing access to the workings of the models, and their underlying assumptions (e.g. via the internet), to show how they actually work. SUMMARY: Constructive discussion and education will help build a consensus on the purposes of STI services, the need for service planning to be evidence-based, and the potential for mathematical tools like DAMs to facilitate this.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.